Temporal Margins and Behavioral Features for Early Risk Assessment in Left-Turn Vehicle and Bicycle Conflicts at Signalized Intersections
Year: 2025
Type: article
Abstract: Between 2019 and 2023, left-turn crashes accounted for 4.5% of traffic accidents in Japan, with 36% of injuries involving cyclists and 66% at signalized intersections. This study quantifies conflict situations between left-turning vehicles and straight-moving bicycles in real-world traffic environments and provides a foundation for determining appropriate timing of future in-vehicle early warning systems. Trajectories reconstructed from seven hours of camera footage yielded six spatio-temporal and behavioral indicators for 37 events with a post-encroachment time (PET) ≤ 3 s. Indicators—PET, time-to-crossing (TTC), right-of-way, urgent braking, deceleration to avoid a crash, and Kalman-based trajectory variance—were statistically related to a composite risk index, R. Approximately 80% of events fell within PETs of 2–3 s, while urgent braking occurred in 50% of cases with PETs of ≤2 s. Each 1 s reduction in PET increased R by 0.18 (R2 = 0.55). PETs ≤ 2.5 s or TTCs ≤ 1.5 s flagged 95% of high-risk events 0.5 s in advance. Joint thresholds involving urgent braking and high variance raised coverage to 100%, with lead times of 0–1.4 s and a false alarm rate of 8%. These findings provide an innovative multi-indicator framework based on real-world trajectories, offering quantitative scenario-specific thresholds for effective in-vehicle warnings at urban intersections.
Source: Machines
Authors: Shuncong Shen, Mitsuki Hashimoto, Shoko Oikawa, Yasuhiro Matsui, Toshiya Hirose
Language: English
Topic: Traffic and Road Safety
Subfield: Safety, Risk, Reliability and Quality
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W4413222593